Decoder and encoder for digital fingerprint codes

Abstract

Decoder and encoder for digital fingerprint codes. A method to encode and decode digital fingerprint codes with an identification encoder and an identification decoder, wherein the digital fingerprint codes comprise a plurality of N-bit data embedded on a set of curves with varying thickness in the curves.

Description

Technical Field

[0001] This invention generally relates to the technical field of encoding and decoding optically machine-readable reproducible (also known as identification code) information that can be read by digital imaging devices, such as digital cameras in mobile phones. Background Technology

[0002] Different types of identification codes are well-known, especially in the graphics industry. One of the oldest types of optically machine-readable reproducible codes is the one-dimensional barcode. These one-dimensional barcodes represent data by varying the width and spacing of parallel lines. Barcodes were originally scanned by special optical scanners (called barcode readers). Later, digital imaging devices and interpretation software became available on devices such as portable mobile devices.

[0003] One-dimensional barcodes have now evolved into two-dimensional barcodes, also known as matrix barcodes such as quick-response codes or QR codes. QR codes were initially designed in Japan for the automotive industry. QR codes on items are scanned by digital imaging devices to read information about the item to which they are attached.

[0004] The ability of portable mobile devices to scan QR codes has made these two-dimensional barcodes increasingly popular. For example, QR codes embedded in Document Markup Language (DOM) documents (such as HTML) contain hyperlinks to web pages. Another example is QR codes printed on packaging (such as medicine packaging containing pharmaceuticals), which, after being scanned, direct the mobile phone operator to the medicine's instructions on a webpage.

[0005] Currently available types of identification codes (such as QR codes) are prominent in document reproduction, making it easier to interpret content embedded in optically machine-readable reproductions.

[0006] Furthermore, the identification code occupies space in the document's layout that could be used for other content, especially in small-scale reproductions such as medicine packaging. Summary of the Invention

[0007] To overcome the above problems, a preferred embodiment of the invention has been implemented using a digital fingerprint code (DF code) encoded in the document as defined in claim 9 and decoded by the digital imaging device as defined in claim 1.

[0008] Embodiments of the present invention provide the ability to add secrets and / or content invisible to the human eye at a certain viewing distance to a document by recognizing codes, and provide the ability to create more space in the document's document space to add more content to the document. Embodiments of the present invention also include a method for easily decoding digital fingerprint codes using a digital imaging device to read content embedded in the digital fingerprint code (DF code).

[0009] The digital fingerprint code includes a set of curves, in which content is embedded by multiple N-bit data (CNT).

[0010] In this context, each possible value of the N-bit data has a thickness (T). N,i ) and length (L) N,i );as well as

[0011] The plurality of N-bit data includes a first N-bit data (N1), followed by different second N-bit data (N2) on the curves of the set of curves; and

[0012] Among them, the value (v) of the first Nth data point (N1) on the curve N,1 coarseness (T) N,i,1 The value (v) is different from the value of the second Nth bit (N2). N,2 coarseness (T) N,i,2 ) and / or the value of the first N-bit data (N1) on the curve (v N,1 ) length (L) N,i,1 The value (v) is different from the value of the second Nth bit (N2). N,2 ) length (L N,i,2 );

[0013] The digital fingerprint code is decoded using an identification and decoding method that includes the following steps:

[0014] - Digital fingerprint codes (DF codes) are captured by digital imaging equipment; and

[0015] - Determine the image capture curve in the digital fingerprint code of the image capture; and

[0016] - Capture two-dimensional points (p) on the curve from the image k The set of ) determines the coarseness (t) of the image capture curve. k The set of ) and

[0017] - Based on the two-dimensional points (p) on the image capture curve k The location and coarseness (t) of the set k The set of N-bit data determines the plurality of N-bit data; and / or

[0018] The digital fingerprint code is encoded using an identification encoding method that includes the following steps:

[0019] - Determine the document; and

[0020] - Identify the curves in the document; and

[0021] - Determine the coarseness (T) for N bits of data from the plurality of N-bit data.N,i ) and length (L) N,i );as well as

[0022] - Determine if it has a defined length (L) N,i The first segment of the curve is determined; and

[0023] - Change the thickness of the portion in the first paragraph to a fixed thickness (T). N,i );as well as

[0024] - Generate a new document from a document that has a generated digital fingerprint code.

[0025] The curves in this invention are not necessarily straight two-dimensional solid lines. The curves have a start point and an end point. The length of the curves is preferably finite and bounded. Furthermore, in a preferred embodiment, the curves are non-self-intersecting curves. Therefore, the curves in this embodiment are continuous, uninterrupted, and bounded. In a preferred embodiment, the set of curves includes a single curve.

[0026] The thickness of the curve derived from this invention can be of any shape, such as triangle, parabola, rectangle, heptagon, pentagon, oval, rhombus, octagon, or ellipse. Determining the thickness of a curve or line is a well-known method, wherein the thickness of the curve or line in the direction perpendicular to the curve or line is measured.

[0027] In the identification and decoding method, a one-dimensional signal is determined based on a plurality of N-bit data from the set of positions and coarsenesses of a set of two-dimensional points on the image-captured curve, wherein the one-dimensional signal varies with the determined coarseness in relation to its determined position. Figure 1 , Figure 2 , Figure 3 Therefore, in a preferred embodiment, based on the two-dimensional points (p) on the image capture curve... k The location and coarseness (t) of the set k The step of determining the plurality of N-bit data from a set of positions includes generating a one-dimensional signal based on the determined set of positions and corresponding coarsenesses. This one-dimensional signal is then converted into the plurality of N-bit data, which is embedded in the digital fingerprint code. This preferred embodiment may further include discretization and / or quantization steps for determining the plurality of N-bit data embedded in the digital fingerprint code.

[0028] In a preferred embodiment, the identification encoding method may include the following steps:

[0029] - Determine the coarseness (T) for the subsequent N bits of N-bit data. N,i ) and length (L) N,i );as well as

[0030] - After the first segment, determine the second segment on the defined curve, where the second segment has a defined length of N subsequent bits of data; and

[0031] - Change the thickness of a portion of the second segment to the thickness determined by the subsequent N bits of data.

[0032] In a more preferred embodiment, a third segment is defined between the first and second segments, and the third segment is defined to have a fixed length and / or a fixed thickness. Preferably, this fixed thickness is different from the thickness (T) of all values ​​of the N-bit data. N,i This makes it easier to distinguish between the subsequent N bits of data during decoding.

[0033] The identification code in this embodiment is called the Digital Fingerprint Code (DF Code).

[0034] In a preferred embodiment, each possible value of the N-bit data has a color (C). N,i ); and among them, the value of the first Nth data point (N1) on the curve (v) N,1 ) color (C N,i,1 The value (v) is different from the value of the second Nth bit (N2). N,2 ) color (C N,i,2 );as well as

[0035] The recognition and decoding method includes the following steps:

[0036] - At a two-dimensional point (p) k Determine the color (c) from the set of ) k The set of ) and

[0037] - Based on coarseness (t) k The set of ) and two-dimensional points on the path (p k The position and color of the set (c) k The set of ) determines the plurality of N-bit data; and / or

[0038] The identification encoding method includes the following steps:

[0039] - Determine color based on N-bit data (C N,i );as well as

[0040] - Change the color of this segment to a specific color (C) N,i ).

[0041] Using color in digital fingerprint codes (DF codes) has a positive impact on the amount of storage on the curve, which is certain when the actual output resolution of the content output device is small.

[0042] The digital fingerprint code (DF code) is preferably an image captured by a digital imaging device included in a mobile device in the identification decoding method; and wherein the mobile device is selected from mobile computers (such as tablet computers) or mobile phones (such as smartphones).

[0043] In a preferred embodiment, a digital fingerprint code (DF code) is used to read information about the item to which the digital fingerprint code is attached.

[0044] In another preferred embodiment, a digital fingerprint code (DF code) is used to track and trace items to which the digital fingerprint code is attached. Tracking and tracing involves the process of determining the current and past locations (and other information) of a unique item or property.

[0045] In another preferred embodiment, a digital fingerprint code (DF code) is used to add security content for anti-counterfeiting purposes to the item to which the digital fingerprint code is affixed. This enhances the anti-counterfeiting effect, wherein the item is a container comprising a liquid, and wherein the digital fingerprint code (DF code) is reproduced using a printer with a liquid mixture of more than 50%. More preferably, the item is a container comprising inkjet ink, and wherein the digital fingerprint code (DF code) is reproduced by an inkjet printer with an inkjet ink mixture of more than 50%. Chemical analysis can compare the liquid used to print the reproduced digital fingerprint code with the liquid inside the container (such as a bottle). Attached Figure Description

[0046] Figure 1 The content is illustrated using multiple binary data (300), which are N-bit data, where N equals 1 in the graph. On the vertical axis (100), the thickness (T) of the N-bit data can be read, for example, in micrometers. N,i ), and on the horizontal axis (200), the position on the curve from a set of curves can be read, for example, in micrometers.

[0047] Figure 1 The chart in the image represents "1100" as multiple binary data. For each bit, the thickness (T) used for the value 1 is... N,1 ) and coarseness (T) for value 0 N,0 ) are different, and for a single bit, the length (L) used for the value 1 N,1 ) and coarseness (L) for value 0 N,0 The two sets of binary data are equal. Between the two subsequent binary data, a fixed thickness and a fixed length are indicated.

[0048] Figure 2The content is illustrated using multiple binary data (300), which are N-bit data, where N equals 1 in the graph. On the vertical axis (100), the thickness (T) of the N-bit data can be read, for example, in micrometers. N,i ), and on the horizontal axis (200), the position on the curve from a set of curves can be read, for example, in micrometers.

[0049] Figure 2 The chart in the image represents "100100" as multiple binary numbers (300). For each bit, the thickness (T) is used for the value 1. N,1 ) and coarseness (T) for value 0 N,0 ) are different, and for a single bit, the length (L) used for the value 1 N,1 ) and coarseness (L) for value 0 N,0 The values ​​are equal. No fixed length is indicated between the two subsequent binary data. The plurality of binary data “100100” in this diagram are encoded plurality of binary data from another plurality of binary data “1100”, wherein the value 1 in the encoded plurality of binary data represents a change in one bit of the other plurality of binary data, and wherein the number of zeros in the encoded plurality of binary data represents how many times the changed bit of the other plurality of binary data is represented. The encoded plurality of binary data is a run-length encoded (RLE) plurality of binary data.

[0050] Figure 3 The diagram illustrates another representation of multiple binary data (300), which are N-bit data, where N equals 1 in the graph. On the vertical axis (100), the coarseness (T) of the N-bit data can be read, for example, in micrometers. N,i ), and on the horizontal axis (200), the position on the curve from a set of curves can be read, for example, in micrometers.

[0051] Figure 3 The diagram in the image illustrates "1100" as multiple binary data. For each bit, the thickness (T) used for the value 1 is... N,1 ) and coarseness (T) for value 0 N,0 ) are different, and for a single bit, the length (L) used for the value 1 N,1 ) and coarseness (L) for value 0 N,0 The two binary data are different. Between the two subsequent binary data, it represents fixed thickness and fixed length.

[0052] Figure 4 The figure shows curve (400) in the digital fingerprint code (500), where multiple binary data "1100" are represented by their position in the fingerprint code. Figure 3The way defined in the text is used to represent it. For a single bit, the coarseness (406, T) is used for the value 1. N,1 ) and coarseness (405, T) for value 0 N,0 ) are different, and for a single bit, the length used for the value 1 is (406, L) N,1 ) and the length (405, L) used for the value 0 N,0 They are different. Between two subsequent binary data, a fixed length is indicated.

[0053] Figure 5 The figure shows curve (400) in the digital fingerprint code (500), where the coarseness (406, T) is used for the value 1 for one bit. N,1 ) and coarseness (405, T) for value 0 N,0 ) are different, and for a single bit, the length used for the value 1 is (406, L) N,1 ) and coarseness (405, L) for value 0 N,0 The two binary data are different. Between the two subsequent binary data, there is a fixed length. The multiple binary data represent the character "A" (uppercase a), which is 65 in ASCII characters and is represented as the byte "01000001". By using the Hamming method as the error correction code method, the multiple binary data embedded on the curve (400) becomes "10011001101001".

[0054] Figure 6 The figure shows curve (400) in the digital fingerprint code (600), where the coarseness (406, T) is used for the value 1 for one bit. N,1 ) and coarseness (405, T) for value 0 N,0 ) are different, and for a single bit, the length used for the value 1 is (406, L) N,1 ) and coarseness (405, L) for value 0 N,0 The two binary data are different. Between the two subsequent binary data, there is a fixed length. The multiple binary data represent the character "A" (uppercase a), which is 65 in ASCII characters and is represented as the byte "01000001". By using the Hamming method (7,4) as the error correction code and adding the header sequence "0001" and the tail sequence "0000", the multiple binary data embedded on the curve (400) becomes "1101001 1001100 11010010000000". The curve (400) in the digital fingerprint code (500) is spiral.

[0055] Figure 7The diagram illustrates a portion of an identification decoding method, which includes an example of processing for decoding a digital fingerprint code using embedded content on a spiral. In a first step, a digital fingerprint code is captured by a digital imaging device (602), which, for example, yields an image-captured digital fingerprint code (605). As a second step, a threshold is determined for the captured digital fingerprint code (612), resulting in, for example, a thresholded image-captured digital fingerprint code (615). In a third step, a blurring method (622) is performed, which, for example, results in a blurred image-captured digital fingerprint code (625). A fourth step is to perform dilation (632) to, for example, obtain a dilated blurred thresholded image-captured digital fingerprint code (635). After this step, an image capture curve in the image-captured digital fingerprint code is determined.

[0056] Figure 8 The figure illustrates a digital fingerprint code (DF code) (500) with a spiral shape as a curve (400), where the thickness (406, T) is used for the value 1 for one bit. N,1 ) and coarseness (405, T) for value 0 N,0 ) are different, and for a single bit, the length used for the value 1 is (406, L) N,1 ) and coarseness (405, L) for value 0 N,0 They are different. Between two subsequent binary data, a fixed length is indicated.

[0057] Figure 9 The figure illustrates a digital fingerprint code (DF code) (500) with multiple curves (400), where the coarseness (406, T) is used for the value 1 for one bit. N,1 ) and coarseness (405, T) for value 0 N,0 ) are different, and for a single bit, the length used for the value 1 is (406, L) N,1 ) and coarseness (405, L) for value 0 N,0 They are different. Between two subsequent binary data, a fixed length is indicated.

[0058] Figure 10The diagram illustrates the user interface (910) of a preferred identification encoder, comprising multiple user interface objects (900, 901, 902, 903, 904, 905, 906, 907, 908, 909). User interface object (909) is the title bar of a window, which includes a close button (“X”) for closing the user interface (910). User interface 901 defines two input fields to define the width and height of the digital fingerprint code (DF code), both in pixels. User interface object (902) includes multiple input fields such as the thickness and length of value 1 (“bit”) and the thickness and length of value 0 (“zero bit”), as well as the length between two subsequent binary data. User interface object (903) includes an input field for the curvature of a spiral as a curve in the digital fingerprint code. User interface object (904) includes an input field for content that must be embedded in the digital fingerprint code (DF code). User interface object (905) includes checkboxes if the content must be encrypted with a key that must be entered in the input fields. The user interface object (906) defines the shape of the curve: a spiral or a sine (“sine”). The user interface object (907) includes an image representing the generated digital fingerprint code (DF code). The user interface object (908) includes the name (“encrypted.jpg”) and location of the digital fingerprint code (DF code) on the hard disk drive (HDD), and the user interface object (909) includes a button for starting the generation of the digital fingerprint code (DF code).

[0059] definition

[0060] document

[0061] A document comprises content, preferably arranged graphically, within a document space. The document is digitally stored in storage units such as hard disk drives (HDDs) connected to a hardware configuration (such as a computer), or memory included in a central processing unit (CPU) within the hardware configuration. The graphical arrangement (also called layout) of the content within the document space is also referred to as the document's layout.

[0062] Documents may include static layouts or, preferably, dynamic layouts. Static layout design may involve more graphic design and visual arts techniques; while dynamic layout design may involve more interactive design and content management techniques to thoroughly anticipate content changes.

[0063] The document space of a document can be a two-dimensional space with two fixed dimensions. More preferably, the document space is a page or multiple pages, and most preferably a webpage.

[0064] Document space can be a two-dimensional space with one fixed and one infinite dimension, such as the multi-print rendering method disclosed in EP 1933257 (Agfa Graphics NV).

[0065] Content objects in a document can be defined by one or more content objects (also known as document objects), such as photographic images, business charts, text, and labels, using one or more colors.

[0066] Raster graphics, also known as bitmaps, continuous tones, or bitmap graphics, represent two-dimensional discrete images P(x,y).

[0067] Vector graphics, also known as object-oriented graphics, use geometric primitives such as points, lines, curves, and shapes or (one or more) polygons, all based on mathematical expressions to represent images.

[0068] Content objects in the document can be defined in vector graphics formats (also known as line-work formats) such as Scalable Vector Graphics (SVG) or AutoCAD Drafting Exchange Format (DXF), and more preferably in Page Description Languages ​​(PDLs), such as Printer Command Language (PCL) developed by Hewlett-Packard, Postscript (PS) developed by Adobe Systems, or Portable Document Format (PDF) developed by Adobe Systems. Preferably, in formats such as Adobe InDesign... TM Adobe PageMaker TM QuarkXpress TM Alternatively, you can create the document layout using a desktop printing (DTP) software package such as Scribus (http: / / scribus.net / canvas / Scribus).

[0069] The content objects in a document can be defined using a document markup language (also known as a markup language, such as IBM's Generalized Markup Language (GML) or Standard Generalized Markup Language (ISO 8879:1986 SGML)), more preferably using Hypertext Markup Language (HTML), and most preferably using HTML5 (the fifth revision of the HTML standard (created in 1990 and standardized to HTML 4 in 1997), and HTML5 was a candidate recommendation of the World Wide Web Consortium (W3C) as of December 2012). Such documents are sometimes called web documents.

[0070] Cascading Style Sheets (CSS), a style sheet language used to describe document content in document markup languages, can be used to create the layout of web documents in web design software packages. More preferably, Cascading Style Sheets 3 (CSS3), published by the CSS Working Group of the World Wide Web Consortium (W3C), can be used to create the layout of web documents in web design software packages.

[0071] The content objects in the document can be defined using Variable Data Printing Format (VDP), such as Intelligent Printer Data Stream (IPDS) found in AS400 and IBM mainframe environments and used with dot matrix printers, Variable Data Intelligent PostScript Printable (VIPP) traditionally used in the transactional black and white printing market: a proprietary VDP language from Xerox, Variable Print Specification (VPS): a VDP language from Creo, Advanced Functional Presentation (AFP) format defined by the AFP Consortium (AFPC), more preferably using Personalized Print Markup Language (PPML), an XML-based industry standard printer language for variable data printing defined by the Print on Demand Initiative (PODi), and most preferably using PDF / VT published in 2010 as ISO 16612-2.

[0072] In a preferred embodiment, the document is defined using a document format selected from vector graphics formats, document markup languages, or variable data printing formats, more preferably from page description formats, variable data printing formats, or document markup languages, and most preferably from portable document format (PDF) or the fifth revision of Hypertext Markup Language (HTML5).

[0073] Raster image processing methods

[0074] Raster image processing methods are image processing methods that interpret documents to render the interpretation of the document into the following:

[0075] - A raster graphic suitable for viewing on a display device, such as a television, computer monitor, or display device for a tablet computer or mobile phone; or

[0076] - A raster pattern suitable for projection using a projector device, such as a video projector, LCD projector, DLP projector, LED projector, or laser diode projector; or

[0077] - Raster graphics, which are suitable for printing on printer equipment such as toner-based printers, inkjet printers, or offset printing presses.

[0078] A content output device is a device that reproduces the content data of a document in its document space, such as a display device, a projector device, or a printer device.

[0079] The digital fingerprint code can be reproduced on a content output device using raster image processing methods. Preferably, the digital fingerprint code is reproduced on a projector device using a projection method, more preferably on a display device using a display method, and most preferably on a printer device using a printing method.

[0080] Raster imaging is a computer-implemented method that executes on hardware (HW) configurations such as computers, tablet computers, etc., including a central processing unit (CPU), memory, storage devices such as hard disk drives (HDDs), and communication interface (IF) devices that send and receive data to and from other hardware configurations via a network. The hardware configuration may include user interface (UI) devices, which may include display devices.

[0081] The apparatus that performs raster image processing methods is called a raster image processor (RIP). A raster image processor (RIP) may include a pre-compression workflow system, such as the PrinectWorkflow System from Heidelberger Druckmaschinen AG. TM Or Apogee Prepress from Agfa Graphics NV TM Or the pre-compression workflow system disclosed in US20130194598 (FUJI XEROX).

[0082] In a preferred embodiment, the raster image processor includes one or more GPUs for rendering documents to a content output device more quickly.

[0083] Identification encoder

[0084] An identification encoder is a device that generates a digital fingerprint code in a document, for example, to identify items (e.g., on a label) attached to the document. The digital fingerprint code can then be read by a digital imaging device to identify the item.

[0085] A recognition encoder is also called a recognition code generator or recognition code writer.

[0086] The identification coding method, also known as the identification code writing method or identification code generation method, is a computer-implemented method executed on hardware (HW) configurations such as computers, tablet computers, etc., including a central processing unit (CPU), memory, storage devices such as hard disk drives (HDDs), and communication interface (IF) devices that send and receive data to and from other hardware configurations via a network. The hardware configuration may include user interface (UI) devices, which may include display devices.

[0087] In a preferred embodiment, the identification encoder includes one or more GPUs for writing digital fingerprint codes into the document more quickly.

[0088] In a preferred embodiment, the identification encoder includes a raster image processor for representing a new document of an embodiment on a content output device such as an inkjet printer, and in a more preferred embodiment, the content output device such as an inkjet printer includes an identification encoder.

[0089] The encoder can also be included in applications such as Adobe InDesign. TM Adobe PageMaker TM QuarkXpress TM Alternatively, it can be implemented in desktop printing (DTP) software packages such as Scribus (http: / / scribus.net / canvas / Scribus), where digital fingerprint codes (DF codes) can be written into documents laid out within the DTP software package.

[0090] The identification and encoding method for digital fingerprint codes includes the following steps in a preferred embodiment:

[0091] - Determine the document; and

[0092] - Identify the curves in the document; and

[0093] - Determine the coarseness (T) for N bits of data from the plurality of N-bit data. N,i ) and length (L) N,i );as well as

[0094] - Determine if it has a defined length (L) N,i The first segment of the curve is determined; and

[0095] - Change the thickness of the first segment to a fixed thickness (T) N,i );as well as

[0096] - Generate a new document from a document with a written digital fingerprint code.

[0097] In a preferred embodiment, a content output device such as an inkjet printer is used to reproduce the new document with a digital fingerprint code.

[0098] The defined curve in the document could be, for example, a segmented outline of the font derived from the text content of the document. Or it could be, for example, the edge of the shell (house) in an image that is the content object of the document.

[0099] In a preferred embodiment, in the identification encoding method, a portion of the first segment is the entire first segment.

[0100] In the recognition encoding method, the thickness of the first segment can be changed at the first side of the curve, but preferably at both sides of the curve.

[0101] The curve in the document is preferably determined by the operator of the encoder, but more preferably automatically by interpreting the content objects in the document. If the content objects are vector graphics, the interpretation of the content objects can be easily performed to automatically determine the curve, since vector graphics are defined by curves such as Bézier curves. If the content objects are raster graphics, the interpretation of the content objects can be performed using image processing methods such as edge detection methods.

[0102] In a preferred embodiment, changing the thickness of a segment includes changing the color of the thickness in the color of a defined curve.

[0103] Changing the thickness of a segment within a vector graphic-defined curve is straightforward because the segment is also defined as a vector graphic. If the segment is a raster graphic-defined curve, image processing methods such as bicubic scaling can be used to change the segment's thickness.

[0104] An overview of image processing methods that may be included in recognition encoders is disclosed in PRATT, William K. Digital Image Processing: PIKS Scientific Inside. 4th edition. John Wiley’s Part 3 “Discrete two-dimensional processing” [145-244] and Part 4 “Image improvement” [245-418].

[0105] The identification encoder may include a data compressor for compressing the plurality of N bits, such as run-length encoding, and / or may include a data security system, wherein the plurality of N bits are securely encoded with a security key, such as a password.

[0106] In a preferred embodiment, the bold shape in the curve of the digital fingerprint code is a triangle, parabola, rectangle, heptagon, pentagon, oval, rhombus, octagon, or ellipse.

[0107] In a preferred embodiment, the document is a wood grain pattern, such as a decorative pattern, and the curves in the set of curves represent nerves or wood grain defects in the wood grain pattern.

[0108] The digital fingerprint code (DF code) recognition encoder, in a preferred embodiment, includes the following steps:

[0109] - Identify decorative patterns that include wood grain patterns; and

[0110] - Identify nerves or grain defects in the wood grain pattern; and

[0111] - Determine the coarseness (T) for N bits of data from the plurality of N-bit data. N,i ) and length (L) N,i );as well as

[0112] - Determine if it has a defined length (L) N,i The first segment of the nerve or the first segment of the wood grain defect; and

[0113] - Change the thickness of this segment to a specific thickness (T) N,i );as well as

[0114] - Generate new wood patterns from wood patterns with digital fingerprint codes.

[0115] The thickening on nerve or wood grain defects derived from the digital fingerprint code (DF code) preferably has the same color as the nerve or wood grain defect.

[0116] Image analysis methods, including Fast Fourier Transform (FFT), histogram calculation, and filtering, can be used to determine neural or grain defects in wood patterns.

[0117] In a preferred embodiment, a digital fingerprint code (DF code) is used to read information about a decorative workpiece that includes a wood pattern as a decorative motif (on which the digital fingerprint code is attached).

[0118] In another preferred embodiment, a digital fingerprint code (DF code) is used to track and trace decorative processed parts, including wood patterns as decorative patterns (on which the digital fingerprint code is attached).

[0119] In a preferred embodiment, an inkjet printer or a gravure printer is used to reproduce the new wood pattern with a digital fingerprint code, and in a more preferred embodiment, an identification encoder is included in the manufacture of the decorative workpiece, wherein an inkjet printer or a gravure printer is used to reproduce the new wood pattern with a digital fingerprint code embedded in the decorative workpiece.

[0120] The identification coding method used for digital fingerprint codes can be included in the manufacture of decorative processed parts.

[0121] In another preferred embodiment, the identification encoding method identifies the curves in a logo included as a content object in the document. A logo is a graphic mark or emblem generally used by businesses, organizations, and even individuals to help and facilitate immediate public recognition. A logo can be purely graphic (symbol / icon) or consist of the organization's name (in conjunction with type or wordmark).

[0122] In a preferred embodiment, the reproduced digital fingerprint code is attached to a security item, such as an identity card (IC) or driver's license. The embodiment includes a security item containing the reproduced digital fingerprint code.

[0123] In another preferred embodiment, the reproduced digital fingerprint code is attached to the workpiece or its packaging (such as pharmaceutical packaging). This enables the possibility of tracking and tracing the workpiece or workpiece contained in the packaging, or the possibility of adding security information to the workpiece or its packaging. The digital fingerprint code can be embedded in the design of the packaging, making it difficult to detect and reproduce by other suppliers. Examples include workpieces such as decorative workpieces or packaging of workpieces that include reproduced digital fingerprint codes.

[0124] In another preferred embodiment, a replicable digital fingerprint code is attached to food packaging, such as carrot packaging. This enables the possibility of tracking and tracing the food contained in the packaging or adding security information to the food packaging. The digital fingerprint code can be embedded in the packaging design, making it difficult to detect and reproduce by other suppliers, thus overcoming counterfeiting. An example is a food package including a replicable digital fingerprint code.

[0125] In another preferred embodiment, the reproducible digital fingerprint code is attached to the packaging of application software on a data storage device, such as the packaging of an operating system on a compact disc read-only memory (CD-ROM). This enables the possibility of tracking and tracing the application software or adding security information to the packaging of the application software on the data storage device. The digital fingerprint code can be embedded in the design of the packaging, making it difficult to detect and reproduce by other vendors. An embodiment is the packaging of application software on a data storage device that includes the reproducible digital fingerprint code.

[0126] In another preferred embodiment, a reproduced digital fingerprint code is attached to a medical device, such as a digital radiography (DR) panel. This enables the possibility of tracking and tracing the medical device or adding security information to it. The digital fingerprint code can be attached to the medical device to make it difficult to detect and difficult to reproduce, thus overcoming counterfeiting. An embodiment is a medical device including a reproduced digital fingerprint code.

[0127] Another embodiment is a container comprising a liquid, wherein the container includes a digital fingerprint code.

[0128] Recognition Decoder

[0129] To decode a digital fingerprint code, a decoder is needed to identify, for example, the item to which the digital fingerprint code is attached. A decoder is also called a fingerprint reader or fingerprint interpreter.

[0130] The identification and decoding method, also known as the identification code reading method or identification code interpretation method, is a computer-implemented method executed on hardware (HW) configurations such as computers, tablet computers, etc., including a central processing unit (CPU), memory, storage devices such as hard disk drives (HDDs), and communication interface (IF) devices that send and receive data to and from other hardware configurations via a network. The hardware configuration may include user interface (UI) devices, which may include display devices.

[0131] In a preferred embodiment, the identification decoder includes one or more GPUs for faster reading of captured digital fingerprint codes, which are digital fingerprint codes (DF codes) on the reproduction of a document captured by a digital imaging device.

[0132] The identification decoder preferably includes transmission components such as a USB cable and a USB connector, as well as memory components for transmitting images from a digital imaging device to capture digital fingerprint codes and performing image processing on the images to capture digital fingerprint codes. More preferably, the identification decoder includes a digital imaging device.

[0133] A decoder for recognizing digital fingerprint codes may include the following steps:

[0134] - Digital fingerprint codes (DF codes) are captured by digital imaging equipment; and

[0135] - Determine the image capture curve in the digital fingerprint code of the image capture; and

[0136] - Capture two-dimensional points (p) on the curve from the image k The set of ) determines the coarseness (t) of the image capture curve. k The set of ) and

[0137] - Based on the two-dimensional points (p) on the image capture curve k The location and coarseness (t) of the set k The set of N-bit data determines the plurality of N-bit data.

[0138] The determination of the image capture curve is performed by the curve searcher. The determination of two-dimensional points (p) on the image capture curve is performed by the coarse quantizer. k Determine the coarseness (t) from the set of ) kA set of ). The interpreter executes the code based on coarseness (t). k The set of N-bit data is used to determine the plurality of N-bit data.

[0139] Before determining the image capture curve in the image capture digital fingerprint code, the operator of the encoder can select the region of interest of the image capture digital fingerprint code, or can zoom in on the image capture digital fingerprint code, for example, up to the boundary of the digital fingerprint code in the image capture digital fingerprint code. This enhances the speed of decoding the digital fingerprint code.

[0140] Image analysis methods, including Fast Fourier Transform (FFT), histogram calculation, and filtering, can be used to determine the image capture curve in the digital fingerprint code of the image capture.

[0141] The multiple N-bit data can be converted into the content of the digital fingerprint code (CNT). This step is also known as the N-bit data decoding step of the digital fingerprint code (DF code). This decoding step is performed by a converter.

[0142] In a preferred embodiment, the content is analyzed after the digital fingerprint code decoding step, and includes a step of selecting an action from a set of actions based on the analysis. An action could be, for example, opening a webpage with the content (CNT) from the image capture digital fingerprint code as its address.

[0143] In another preferred embodiment, the plurality of N-bit data are analyzed, and the step of selecting an action from a set of actions based on the analysis is included.

[0144] Image captures two consecutive two-dimensional points (p) on the curve k The distance between the N bits is preferably less than 10 times the minimum pixel width or height of the captured digital fingerprint code, more preferably less than 5 times the minimum pixel width or height of the captured digital fingerprint code, and most preferably less than 2 times the minimum pixel width or height of the captured digital fingerprint code, because this ensures better sampling of the image capture curve from the digital fingerprint code, thus making it easier to generate a one-dimensional signal and determine the plurality of N bits from the identification code embedded in the digital fingerprint code.

[0145] In the decoding step, the plurality of N-bit data may be decompressed and / or decrypted and / or error-corrected to convert the plurality of N-bit data into the content of a digital fingerprint code (CNT). The error correction of the plurality of N-bit data is preferably based on the error-coded codes included in the plurality of N-bit data.

[0146] In a preferred embodiment, a plurality of two-dimensional points (p) are used. k The path (P) is used to approximate the image capture curve; and in which, at two-dimensional points (p... k From the set of ), determine the coarseness (t) k A set of ).

[0147] Another preferred embodiment may include the following steps:

[0148] - Approximately includes multiple two-dimensional points (p) k The skeleton (S) of the image capture curve in the digital fingerprint code of the image capture is used. This skeleton (S) can be converted into a path (P) to approximate the image capture curve.

[0149] To easily determine the two-dimensional points (p) on the image capture curve k The set of curves in a digital fingerprint code, where the curves may not intersect each other and / or may not intersect themselves. In this embodiment, the curves are non-self-intersecting curves in a preferred embodiment.

[0150] The skeleton of an image capture curve is a thinner version of that shape, equidistant from the boundaries of the image capture curve. The skeleton typically emphasizes the geometric and topological properties of the image capture curve, such as its continuity, topology, length, orientation, and width. It serves as a representation of the image capture curve.

[0151] A method for determining the skeleton is disclosed in Chapter 5 of JR Parker’s Algorithms for Image Processing and Computer Vision (John Wiley, ISBN 0471140562).

[0152] The skeleton (S) to path (P) of the image capture curve in the preferred embodiment is transformed using a tracing method, also known as a vectorization method. The tracing method preferably includes an edge detection algorithm.

[0153] To achieve fast reading of captured digital fingerprint codes, distance skeleton algorithms (such as the fast parallel algorithms for thinning digital patterns developed by TY ZHANG and CY SUEN) are used. Communications of the ACM. The Zhang-Suen parallel thinning method disclosed in 1984, vol.27, No.3, pp.236-239, is used to determine the skeleton of the image capture curve.

[0154] Before determining the image capture curve, the image capture digital fingerprint code can be converted into an indexed color image and, more preferably, a binary image. The conversion to indexed color makes it easier to detect the image capture curve using image processing methods such as edge detection.

[0155] The same digital fingerprint code can be captured using, for example, different lighting conditions. Furthermore, different resolutions of digital imaging devices, such as the angle at which the digital fingerprint code is acquired, can provide different algorithms to ensure that the identification is readable for a set of digital imaging devices. This is why, in a preferred embodiment, the captured digital fingerprint code is converted into an indexed color image (such as a binary image), thus making the determination of the image capture curve easier and faster.

[0156] Morphological image methods can be used to deform the image capture curve and / or the image capture digital fingerprint code, such as by dilation, scaling, rotation, translation, and warping, to enhance the rapid determination of the image capture curve of the digital fingerprint code.

[0157] The morphological approach to images is disclosed in JR PARKER's Algorithms for Image Processing and Computer Vision (John Wiley. ISBN0471140562), and especially in Chapters 2 and 3.

[0158] By tracing the image capture curve or skeleton (S) or path (P), the thickness and length of the thickness in the image capture curve are determined at multiple points. In embodiments of the recognition decoder, these determinations are made for multiple N-bit data.

[0159] If in the preferred embodiment there is color (C) for each value of N-bit data... N,i Then, the tracking, thickness, length of the thickness, and color of the image capture curve or skeleton (S) or path (P) are determined at multiple points.

[0160] In a preferred embodiment, the digital fingerprint code is embedded in a nerve or wood grain defect within a decorative pattern included in a decorative finished part (such as a decorative panel) that incorporates a wood grain pattern as a decorative motif. Therefore, in a preferred embodiment, the identification decoding method includes the following steps:

[0161] - Capture decorative patterns in decoratively finished parts; and

[0162] - Identify image capture neural pathways or image capture wood grain defects in image capture decorative patterns; and

[0163] - Capturing two-dimensional points on neurons from images (p k The set of ) determines the coarseness (t) of the image-capturing neural network. k The set of ) and

[0164] - Based on image capture of neural pathways or image capture of two-dimensional points on wood grain defects (p k The location and coarseness (t) of the set kThe set of N-bit data determines the plurality of N-bit data.

[0165] As a substitute for nerves, curves can be any wood grain defect, such as knots or cracks in the wood grain pattern.

[0166] Nerves are the grain lines in the wood pattern caused by the annual rings (especially the smaller annual rings) in the wood.

[0167] Digital fingerprint code

[0168] The digital fingerprint code (DF code) is an optically machine-readable reproducible content (CNT). In this embodiment, the digital fingerprint code can be read by a digital imaging device.

[0169] In this embodiment, the digital fingerprint code embeds multiple N-bit data to represent content (CNT). From 0 to (2... N -1) Select N values ​​from the data, and therefore there are two to the power of N possible values. N is a positive natural number and N is greater than zero.

[0170] The content may include the serial number, code name, and date (such as the date of reproduction) of the item to which the digital fingerprint code is attached. The content may also include the reproduction characteristics of the digital fingerprint code.

[0171] The plurality of N-bit data are preferably a plurality of hexadecimal numbers (N=4), more preferably a plurality of octal numbers (N=3), and most preferably a plurality of binary data (N=1), also referred to as a bit stream.

[0172] The greater the number of possible values ​​in the N-bit data in this embodiment, the higher the storage capacity of the digital fingerprint code.

[0173] Storage capacity limits the maximum number of bits that can be embedded in a digital fingerprint (DF) code of multiple N-bit data. Storage capacity is sometimes limited by the maximum number of bytes that can be embedded in a digital fingerprint (DF) code of multiple N-bit data.

[0174] The greater the total length of a set of curves in the embodiment, the higher the storage capacity of the digital fingerprint codes on that set of curves.

[0175] In a preferred embodiment, the storage capacity of the digital fingerprint code on the set of curves is between 1 and 10 bits per millimeter, more preferably between 1 and 20 bits per millimeter, and most preferably between 1 and 50 bits per millimeter.

[0176] Minimum coarseness (T) of values ​​from N-bit data N,i The smaller the length (L) and the minimum length (L) N,i The smaller the value (e.g., due to the larger output resolution of the content output device), the larger the storage capacity of the digital fingerprint code.

[0177] In a preferred embodiment, the digital fingerprint code (DF code) is visible to the human eye only at an observation distance between 0 mm and 200 mm, more preferably between 0 dm and 50 mm, and most preferably between 0 dm and 10 mm.

[0178] The plurality of N-bit data may include a header sequence of N-bit data for easier identification of the beginning of the plurality of N-bit data and / or a tail sequence of N-bit data for easier identification of the end of the plurality of N-bit data. Preferably, the header sequence and / or the tail sequence have a fixed size.

[0179] The plurality of N-bit data may include a sequential sequence of N-bit data used to identify the order of curves from a set of curves in this embodiment. This sequential sequence is used to sort the set of the plurality of N-bit data from each curve and connect them in the correct order into a set of the plurality of N-bit data.

[0180] The plurality of N-bit data may include error-correcting codes. The error-correcting codes may include parity checks and / or checksums used to improve the error-correcting codes.

[0181] Error correction codes are implemented by adding redundancy, for example by adding extra entries to the Content-Number To-The-Counter (CNT) (which the recognition decoder can use to check the consistency of the CNT and recover data determined to be corrupted). In a preferred embodiment, the plurality of N-bit data includes Hamming codes as error correction codes. An example of a high-speed Hamming code circuit is disclosed in US 4276647 (XEROX CORPORATION).

[0182] The error correction capability in the digital fingerprint code (DF code) is advantageous if the reproduction of the digital fingerprint code (DF code) in the embodiment is not clean or is damaged.

[0183] The plurality of N-bit data may include compressed N-bit data compressed by a data compression method such as run-length encoding. Preferably, the compressed N-bit data is compressed using a lossless data compression method. Lossless data compression methods utilize statistical redundancy to represent data more concisely without loss of information, making the process reversible by decompression.

[0184] The digital fingerprint code in this embodiment includes a set of curves.

[0185] Content is embedded through multiple N-bit data (CNT).

[0186] In this context, each possible value of the N-bit data has a coarseness (T). N,i ) and length (L) N,i );as well as

[0187] The plurality of N-bit data includes a first N-bit data (N1), followed by different second N-bit data (N2) on the curves of the set of curves; and

[0188] Among them, the value (v) of the first Nth data point (N1) on the curve N,1 coarseness (T) N,i,1 The value (v) is different from the value of the second Nth bit (N2). N,2 coarseness (T) N,i,2 ) and / or the value of the first N-bit data (N1) on the curve (v N,1 ) length (L N,i,1 The value (v) is different from the value of the second Nth bit (N2). N,2 ) length (L N,i,2 ).

[0189] In a preferred embodiment, the plurality of N-bit data includes more than two N-bit data.

[0190] For clarity, it should be understood that the curve is not necessarily a straight two-dimensional solid line. The curve has a start point and an end point. The start point and end point can be the same, such as a circular curve. The length of the curve is preferably finite and bounded. In a preferred embodiment, the digital fingerprint code comprises a set of non-self-intersecting curves, wherein the content embedded (CNT) is comprised of multiple N-bit data having more than two N-bit data bits. The curves in this embodiment are continuous and uninterrupted.

[0191] Coarseness (T) for each possible value of N-bit data N,i ) and length (L) N,i This gives the possibility of obtaining a one-to-one relationship between coarseness and length and the value of N-bit data.

[0192] Coarseness (T) N,i Preferably, the diameter is between 0.002 mm and 5 mm, more preferably between 0.005 mm and 5 mm, and most preferably between 0.005 mm and 2 mm.

[0193] Length (L) N,i Preferably, the diameter is between 0.002 mm and 5 mm, more preferably between 0.005 mm and 5 mm, and most preferably between 0.005 mm and 2 mm.

[0194] Minimum coarseness (T) N,i ) and minimum length (L) N,i The quality depends on the actual output resolution of the content output device and the quality of the reproduction of the digital fingerprint code (DF code).

[0195] As an example of a preferred embodiment, a 100% black digital fingerprint printing code is printed at 4000 dpi using offset printing equipment. A pixel is a minimum of 0.00635 millimeters (mm), but in order to detect the thickness on the curve using a preferred recognition decoding method, the minimum thickness is 4 pixels (which is 0.0254 mm) and more preferably 16 pixels (which is 0.1016 mm).

[0196] Suppose that a digital fingerprint code is printed using offset printing equipment at 10160 dpi. A pixel is a minimum of 0.0025 mm, but in order to detect the thickness on the curve using a preferred recognition and decoding method, the minimum thickness is 4 pixels (which is 0.01 mm) and more preferably 16 pixels (which is 0.04 mm).

[0197] In a preferred embodiment, the minimum thickness of the N-bit value used in the digital fingerprint code is between 2 and 100 pixels, more preferably between 4 and 50 pixels, and most preferably between 8 and 25 pixels. A larger minimum thickness necessitates lower print quality of the digital fingerprint, but the reproduced fingerprint code is more easily noticed by the human eye.

[0198] In a preferred embodiment, the minimum length of the N-bit value used in the digital fingerprint code is between 2 and 100 pixels, more preferably between 4 and 50 pixels, and most preferably between 8 and 25 pixels. The greater the minimum thickness, the lower the printing quality of the digital fingerprint must be, but the reproduced digital fingerprint code is more easily noticed by the human eye.

[0199] In a preferred embodiment, the digital fingerprint code has a color (C) for each value of the N-bit data. N,i );and

[0200] The value (v) of the first Nth data point (N1) on the curve N,1 ) color (C N,i,1 The value (v) is different from the value of the second Nth bit (N2). N,2 ) color (C N,i,2 ).

[0201] Each value of N-bit data has a color (C N,i Digital fingerprint codes can use only a specific amount of color. Color (C) N,i (Can be selected from a set of colors.)

[0202] Coarseness (T) for each possible value of N-bit data N,i ), length (L) N,i ) and color (C N,i This gives the possibility of obtaining a one-to-one relationship between the value of N-bit data and the thickness, length, and color.

[0203] If the number of curves in a set of curves in a digital fingerprint code is greater than one, then the digital fingerprint code may include another curve.

[0204] The binary code is embedded with multiple M-bit data points containing more than two M-bit data points; and

[0205] Where M is different from N; and

[0206] In this context, each possible value of the M-bit data has a coarseness (T). M,j ) and length (L) M,j ) curve; and

[0207] The plurality of M-bit data includes a first M-bit data (M1), followed by different second M-bit data (M2); and

[0208] Among them, the value (v) of the first M-bit data (m1) on the other curve M,1 coarseness (T) M,j,1 The value (v) is different from the value of the second M-bit data (M2). M,2 coarseness (T) M,j,2 ) and / or the value (v) of the first M-bit data (M1) on another curve. M,1 ) length (L M,j,1 The value (v) is different from the value of the second Nth bit data (M2). M,2 ) length (L M,j,2 ).

[0209] In a preferred embodiment, the digital fingerprint code is included in the document, and in a more preferred embodiment, it is included in the content object of the document.

[0210] The digital fingerprint code is preferably a raster graphic, and more preferably a vector graphic. The digital fingerprint code may include multiple raster graphics and / or multiple vector graphics. For example, the curve is a raster graphic, and the thickness of the curve representing the multiple N-bit data may be multiple vector graphics.

[0211] In a preferred embodiment, the plurality of N-bit data are unipolar line codes. These are the simplest line codes, directly encoding the bit stream, and are similar to on / off keying in modulation.

[0212] Digital imaging equipment

[0213] Digital imaging devices capture images, for example, for reproducing documents, and generate color signals from the images to an output device with specific color sensitivity. A digital imaging device is further one of many devices of the same type useful to the output device. A digital imaging device (e.g., a digital camera) includes a color sensor for capturing images and generating color signals from the captured images, the color sensor having a predetermined spectral sensitivity, and optics inserted into image light directed towards the color sensor, the optics also having predetermined spectral characteristics. The combination of the spectral sensitivity of the color sensor and the spectral characteristics of the optics uniquely distinguishes this particular digital imaging device from other digital imaging devices of the same type.

[0214] In a preferred embodiment, the digital imaging device includes a charge-coupled device (CCD) camera, which is a digital video camera that feeds its images to a computer or computer network in real time, such as an IP camera (which uses a direct connection utilizing Ethernet or WiFi) or a network camera connected by a USB cable, FireWire cable, or similar cable. Such network cameras are preferably included in mobile phones or mobile computers such as tablet computers.

[0215] In another preferred embodiment, the digital imaging device is a digital microscope, which includes a charge-coupled device (CCD) camera that feeds its image to a computer or computer network in real time after the image has been magnified by an optical system by more than eight times, preferably more than 30 times. The maximum magnification of the digital microscope is preferably greater than 30 times, more preferably greater than 50 times, and most preferably greater than 100 times. If the digital fingerprint code is small, it must be captured and reproduced by the digital imaging device via the optical system; otherwise, the identification decoder may not read the plurality of N bits of data embedded in the digital fingerprint code.

[0216] Digital imaging devices may include complementary metal-oxide-semiconductor (CMOS) sensors.

[0217] Preferably, the digital imaging device includes an illumination device (such as a light-emitting diode (LED) flash) to capture the digital fingerprint code of this embodiment using the light from the illumination device in low-light conditions.

[0218] To enhance the storage capacity of a set of digital fingerprint codes on a curve, the resolution of the digital imaging device preferably exceeds 5 megapixels (MPx). One megapixel (MPx) is one million pixels and is a term used not only to refer to the number of pixels in an image but also to represent the number of image sensor elements in a digital imaging device or the number of display elements in a display device. For example, the iPhone mobile phone... TM 4. It features a rear-illuminated 5-megapixel rear-facing camera with a 3.85 mm f / 2.8 lens.

[0219] The resolution of the digital imaging device is preferably greater than 8 megapixels and more preferably greater than 12 megapixels.

[0220] The digital imaging device is preferably a three-color digital camera, such as an RGB digital camera.

[0221] Digital imaging apparatuses may include image processing devices for processing captured images (such as captured digital fingerprint codes) before transmitting them to an identification decoder. The image processing devices of a digital imaging apparatus may include one or more GPUs for processing captured images (such as captured digital fingerprint codes) more quickly. An example of processing captured images in a digital imaging apparatus is color conversion (CMS) to a separate color space (such as CIE Lab) or to a dependent color space (such as sRGB as specified in IEC 61966-2-1:1999). Another digital example of processing captured images in a digital imaging apparatus is digitally magnifying the captured image using a deterministic amplifier.

[0222] Digital imaging devices may include image processing devices that perform image processing methods selected from the following: color and / or saturator space transformation (CMS); automatic contrast; unsharpening mask (USM); content object position correction; noise reduction; speckle reduction; applying convolution; rotation; scaling; cropping; speckle reduction; destabilization; projection.

[0223] Content output devices

[0224] A growing number of content output devices (such as display devices, projector devices, and printer devices) have been developed for the reproduction of content such as images and text. Examples of content output devices used to reproduce documents include CRTs, LCDs, plasma display panels (PDPs), electroluminescent displays (ELDs), carbon nanotubes, quantum dot displays, laser TVs, electronic paper, electronic ink, projection displays, conventional photography, electrophotography, dot matrix printers, thermal printers, dye-sublimation printers, and inkjet systems, to name just a few. Furthermore, conventional printing systems such as offset printing, lithography, rotary gravure printing, aniline printing, letterpress printing, and screen printing have been developed for the reproduction of images and / or text, and therefore, content output devices also exist.

[0225] The apparent output resolution of a content output device is determined by the fact that the human eye perceives an image as having more detail than it actually possesses in physical reality (which is limited by the actual output resolution). Apparent and actual output resolution are defined in dots per inch (dpi) (especially for printer devices) and in pixels per inch (ppi) (especially for display devices), and are also known as pixel density. One inch is precisely 25.4 millimeters.

[0226] In a preferred embodiment, the digital fingerprint code is reproduced by a content output device at an actual output resolution of more than 300 dots per inch or 300 pixels per inch. In a more preferred embodiment, the digital fingerprint code is reproduced by a content output device at an actual output resolution of more than 2,400 dots per inch (dpi). In the most preferred embodiment, the digital fingerprint code is reproduced by a content output device at an actual output resolution of more than 4,800 dots per inch (dpi).

[0227] The larger the actual output resolution and apparent output resolution of the content output device, the smaller the digital fingerprint code (DF code) and / or the coarseness difference (T) in the reproducible digital fingerprint code (DF code). N,i The smaller the length difference (L) N,i The smaller the value.

[0228] Smaller digital fingerprint codes and / or smaller coarseness and / or smaller length differences in digital fingerprint codes (DF codes) make it possible, for example, to write and reproduce digital fingerprint codes that are invisible to the human eye at a distance of more than 20 cm (which is the normal reading distance).

[0229] Rotary gravure printing (or simply rotary or gravure printing) is a gravure printing process that involves engraving an image onto an image carrier. In gravure printing, the image is engraved onto a cylinder, and like offset and aniline printing, it uses a rotary printing press. Rotary gravure printing processes using gravure printers are still used in the commercial printing and decorative processing of periodicals, postcards, and corrugated (cardboard) product packaging.

[0230] Offset printing, as an example of a conventional printing system, is a printing technique in which ink is spread in the form of an etched image onto a metal plate, then transferred (offset) to an intermediate rubber pad, and finally transferred to a printing surface by pressing paper against the pad. When printing color images, four plates are typically used, one for each CMYK component. Additionally, speckled colors can be added by adding new layers with the desired specific pigments.

[0231] Modern offset printing systems utilize computer-to-plate (CTP) technology, creating plates directly from computer output, as in older technologies where photographic film was created by a computer and then used to create the plates. Offset printing presses are large, expensive, and complex machines requiring experienced operators to operate. Preparing documents for printing on an offset press is complex because plates must be created, and operators must spend considerable time manually preparing and calibrating the press to achieve the desired results. Even though this process is quite expensive and slow, the actual printing process is inexpensive, fast, and produces high image quality. This makes it a good solution for producing large volumes of copies. For this reason, it has become the most common method of commercial printing and is widely used for printing newspapers, periodicals, books, etc.

[0232] In inkjet systems, which serve as examples of digital printing systems, ink is deposited (also known as jetted) directly onto the substrate, simplifying the printing mechanism and eliminating all processes involved in creating the printing plate. Furthermore, it avoids the extra work that offset operators need to do to prepare the offset printing press for printing. Both of these factors result in shorter turnaround times and a cheaper starting point for customizing single or multiple copies, which is impossible in offset printing because creating different plates for each copy is not feasible.

[0233] Another advantage is the possibility of printing over a wider area (closer to the RGB area) than offset printing. Furthermore, it's easier to print on almost any surface: wood, ceramics, plastics, etc. Offset printing presses have always been considered superior to digital presses such as inkjet systems in terms of resolution and sharpness, although digital presses such as inkjet systems now exist that match the quality of offset presses. Nevertheless, digital printing has certain disadvantages compared to offset printing, which can make the decision to choose one or the other printing method difficult. The resolution of a digital press depends on the dots per inch (dpi) parameter. Even though this parameter has gradually increased in recent years, the quality of digital presses still cannot compare to that of offset presses in terms of resolution and sharpness. Another disadvantage of digital presses is the handling of speckled colors. Typically, digital presses use CMYK pigments to represent all colors. As mentioned, using CMYK can only adequately reproduce a subset of speckled colors. Some sophisticated digital presses use additional fifth or sixth colorants, which help reproduce a larger subset of speckled colors, but are still insufficient to reproduce the entire set well.

[0234] Preferably, offset printing is used to reproduce the digital fingerprint code, and more preferably, inkjet printing is used to reproduce the digital fingerprint code of this embodiment.

[0235] In another preferred embodiment, the digital fingerprint code is reproduced using a microlithography apparatus or a nanolithography apparatus. Microlithography and nanolithography specifically involve lithographic patterning methods capable of structuring materials at fine scales. Typically, features smaller than 10 micrometers are considered microlithography, and features smaller than 100 nanometers are considered nanolithography. Photolithography is one of these two methods (microlithography and nanolithography) commonly used in the manufacture of semiconductors for microchips. Photolithography is also generally used in the manufacture of microelectromechanical systems (MEMS) devices. Photolithography generally uses a pre-fabricated photomask or scribe line as a master from which the final pattern is derived. While photolithography is the most commercially advanced form of nanolithography, other techniques, such as electron beam lithography, are also used to achieve many practical output resolutions (sometimes as small as a few nanometers).

[0236] Graphics processing unit

[0237] Graphics processing units (GPUs) have been used for many years to reproduce computer graphics. Now, they are also used for general-purpose tasks due to their highly parallel architecture, making them more efficient than central processing units (CPUs).

[0238] GPUs can be combined with CPUs to achieve better performance. This way, the serial parts of the code run on the CPU, while the parallel parts are completed on the GPU. While CPUs with multiple cores are available for every new computer and allow for parallel computing, these are concentrated on having a few high-performance cores. GPUs, on the other hand, have an architecture consisting of thousands of lower-performance cores, making them particularly useful when dealing with large amounts of data.

[0239] One of the most popular tools available in the GPU computing market is CUDA. CUDA is developed by Nvidia. TM They create parallel computing platforms and programming models that can only be used on their GPUs. A major advantage of CUDA is its ease of use, employing a language called CUDA C, which is essentially an extension of C, with similar syntax and is very easy to integrate into C / C++ environments.

[0240] The required data is first copied from main memory to GPU memory (①), the CPU sends instructions to the GPU (②), the GPU executes the instructions simultaneously on all parallel cores (③), and the results are copied from GPU memory back to main memory (④).

[0241] CUDA parallel execution units consist of threads divided into blocks. Combining the use of blocks and threads allows for the launch of the maximum number of available parallel units, exceeding 50 million for the largest GPUs. Even with this massive parallel capability, there are situations where the data may exceed the limits. In those cases, the only possibility is to iterate through a grid of millions of parallel units as many times as needed until all the data has been processed.

[0242] path

[0243] In this embodiment, a path is defined as a sequence of at least two two-dimensional points (also called 2D points, which are connected to sub-paths). A sub-path can be a curve defined as a 2D function between 2D points, such as a line, polygon, Bézier curve, or parametric equation. It is not necessary for each sub-path to use the same 2D function. A 2D point is defined as a point with x and y coordinates as used in a Cartesian coordinate system. The 2D points of a path can be referred to as points.

[0244] Decorative images

[0245] Decorative images are images that represent wood, stone, rock, or imaginary patterns.

[0246] Decorative images are created using appropriate commercially available hardware (such as scanning photographs or taking images with a digital camera) and commercially available software (such as Adobe Photoshop for processing and creating decorative images). TM This was achieved through [the process].

[0247] The content of the decorative image is preferably defined in a raster graphics format, such as Portable Network Graphics (PNG), Tagged Image File Format (TIFF), Adobe Photoshop Document (PSD), or Joint Photographic Experts Group (JPEG) or Bitmap (BMP), but more preferably in a vector graphics format, wherein the decorative image, as a raster graphics format, is embedded. Preferred vector graphics formats are Scalable Vector Graphics (SVG) and AutoCAD Drawing Exchange Format (DXF), and most preferably the decorative image is embedded in a Page Description Language (PDL), such as Postscript (PS) or Portable Document Format (PDF).

[0248] Decorative images may be stored as one or more files and / or loaded onto a computer's memory. This embodiment may include a method for loading decorative images into a computer's memory.

[0249] Decorative patterns

[0250] Decorative patterns are derived from regions of interest in decorative images, and variations in the decorative patterns can be achieved by selecting different regions of interest within the decorative image. The ratio of the area of ​​such a region of interest as a decorative pattern to the area of ​​the decorative image is preferably between 50% and 100%, more preferably between 10% and 100%, and most preferably between 1% and 100%. The area containing the content of the region of interest as a decorative pattern is also called the content area. The dimensions of the region of interest and thus the decorative pattern can have a width between 50 mm and 4000 mm and a length between 100 mm and 6000 mm or more.

[0251] Decorative patterns are preferably rectangular, but they can also be triangular, parabolic, rectangular, heptagonal, pentagonal, octagonal, or elliptical. Decorative patterns may have sides with one or more curved sections. The advantage of rectangular decorative patterns is their ease of cutting into decorative finished pieces. Rectangular or non-rectangular decorative patterns can be cut using a cutting plotter. While using a cutting plotter is more time-consuming, non-rectangular decorative patterns increase the amount of decorative finished pieces that can be created, such as mosaic flooring with laminates or designer furniture.

[0252] The content of the decorative pattern is preferably defined in a raster graphics format, such as Portable Network Graphics (PNG), Tagged Image File Format (TIFF), Adobe Photoshop Document (PSD), or Joint Photographic Experts Group (JPEG) or Bitmap (BMP), but more preferably in a vector graphics format, wherein the decorative pattern, as a raster graphics format, is embedded. Preferred vector graphics formats are Scalable Vector Graphics (SVG) and AutoCAD Drawing Exchange Format (DXF), and most preferably the decorative pattern is embedded in a Page Description Language (PDL), such as Postscript (PS) or Portable Document Format (PDF).

[0253] Decorative patterns can be stored as one or more files and / or loaded onto a computer's memory. This embodiment may include a method for loading a decorative pattern into a computer's memory.

[0254] Decorative processed parts

[0255] Decorative finished parts are preferably rigid or flexible panels, but can also be rolled flexible substrates. In a preferred embodiment, the decorative finished parts are selected from the group consisting of kitchen panels, floor panels, furniture panels, ceiling panels, and wall panels.

[0256] In a more preferred embodiment, the decorative processed part includes tongues and grooves that enable glue-free mechanical bonding.

[0257] Decorative finished parts (especially decorative panels) may also include a sound-absorbing layer disclosed in US8196366 (UNILIN).

[0258] In a preferred embodiment, the decorative panel is an antistatic layered panel. Techniques for making the decorative panel antistatic are well known in the field of decorative processed parts, as illustrated in EP1567334 (FLOORING IND).

[0259] In a preferred embodiment, the decorative panel is manufactured in the form of a rectangular elliptical strip. Its dimensions can vary considerably. Preferably, the panel has a length exceeding 1 meter and a width exceeding 0.1 meters; for example, the panel can be approximately 1.3 meters long and approximately 0.15 meters wide. According to a particular embodiment, the panel is longer than 2 meters and preferably has a width of approximately 0.2 meters or more. The decorative pattern of such panels is preferably a free-form repetition.

[0260] Core layer

[0261] The core layer is preferably made of wood-based materials, such as particleboard, MDF or HDF (medium-density fiberboard or high-density fiberboard), oriented strand board (OSB), etc. Furthermore, boards made of synthetic materials or boards hardened by water, such as cement boards, can be used. In a particularly preferred embodiment, the core layer is an MDF or HDF board.

[0262] The core layer may also be assembled from at least multiple sheets of paper or other carrier sheets impregnated with thermosetting resin, as disclosed in WO2013 / 050910 (UNILIN). Preferred paper sheets include so-called kraft paper obtained by chemical pulping (also known as kraft pulping), as disclosed in US 4952277 (BET PAPERCHEM).

[0263] In another preferred embodiment, the core layer is a board material composed primarily of wood fibers bonded together with a condensation adhesive, wherein the condensation adhesive comprises 5 to 20% by weight of the board material and yields at least 40% by weight of wood fibers from recycled wood. Suitable examples are disclosed in EP 2374588 (UNILIN).

[0264] A synthetic core layer may also be used instead of a wood-based core layer, such as those disclosed in US 2013062006 (FLOORING IND). In a preferred embodiment, the core layer comprises a foamed synthetic material, such as foamed polyethylene or foamed polyvinyl chloride.

[0265] Other preferred core layers and their manufacture are disclosed in US 2011311806 (UNILIN) and US 6773799 (DECORATIVESURFACES).

[0266] The core layer thickness is preferably 2-12mm, more preferably 5-10mm.

[0267] Tongue groove contour

[0268] The sides of a set of separate decorative finished parts can be milled to create tongue-like or grooved profiles, allowing decorative finished parts such as pawl laminates (also known as pawl decorative finished parts) to be interconnected. The advantage is ease of assembly, eliminating the need for glue. The shape of the tongue-groove profile required to achieve good mechanical bonding is well-known in the laminate flooring industry, as illustrated in EP 2280130 A (FLOORING IND), WO 2004 / 053258 (FLOORING IND), US 2008010937 (VALINGE), and US 6418683 (PERSTORP FLOORING).

[0269] Method for manufacturing decorative processed parts

[0270] A method for manufacturing decorative processed parts according to a preferred embodiment may include the following steps:

[0271] - Decorative patterns printed using gravure printing; and

[0272] - Paper substrate impregnated with thermosetting resin; and

[0273] - A thermosetting resin-impregnated paper substrate carrying an inkjet-printed decorative pattern is hot-pressed into a decorative workpiece.

[0274] A method for manufacturing decorative processed parts according to a preferred embodiment may include the following steps:

[0275] - Preferably, decorative patterns are inkjet printed on a paper substrate using one or more water-based inkjet printers; and

[0276] - Paper substrate impregnated with thermosetting resin; and

[0277] - A thermosetting resin-impregnated paper substrate carrying an inkjet-printed decorative pattern is hot-pressed into a decorative workpiece.

[0278] In a preferred embodiment, the method for manufacturing decorative processed parts includes the following steps in sequence:

[0279] a) Using one or more water-based inkjet printers to inkjet print decorative patterns on a paper substrate; and

[0280] b) Impregnating inkjet-printed paper substrates with thermosetting resins; and

[0281] c) Hot-press a thermosetting resin-impregnated paper substrate carrying an inkjet-printed decorative pattern into a decorative workpiece.

[0282] In another preferred embodiment, the method for manufacturing decorative processed parts includes the following steps in sequence:

[0283] a) Impregnate the paper substrate with thermosetting resin;

[0284] b) Using one or more water-based inkjet printers to inkjet print decorative patterns on thermosetting resin-impregnated paper; and

[0285] c) Thermosetting paper bearing inkjet-printed decorative patterns is hot-pressed into decorative processed parts. In the latter, financial losses due to cutting errors are minimized.

[0286] A thermosetting resin-impregnated paper carrying an inkjet-printed decorative pattern is hot-pressed between a protective layer containing thermosetting resin and a core layer, with the decorative pattern facing the protective layer. In the latter, the thermosetting resin-impregnated paper preferably includes a whitening agent for masking surface defects in the core layer.

[0287] Alternatively, a thermosetting resin-impregnated paper carrying the decorative pattern is hot-pressed as a protective layer into the decorative workpiece, with the decorative pattern facing the core layer present in the decorative workpiece. The protective layer (or overlay) contains little or no whitening agent because the overlay becomes transparent after hot pressing, allowing the decorative pattern to be observed. The decorative pattern must face the core layer, otherwise it will deteriorate rapidly through wear. In another preferred embodiment, the decorative pattern comprises a white ink layer as the outermost ink layer. The outermost white ink layer refers to the decorative pattern inkjet-printed on the overlay covered by the white ink layer (preferably applied by inkjet printing), but screen printing or offset printing is also possible, for example. By having an outermost white ink layer on the decorative pattern, the paper layer between the core layer and the overlay layer can be omitted, which not only represents a cost benefit but also a simplified manufacturing process.

[0288] In a preferred embodiment of the manufacturing method, the thermosetting resin-impregnated paper includes a colored paper substrate, more preferably a bulk colored paper substrate. The use of a colored paper substrate reduces the amount of ink required to form the decorative pattern.

[0289] In a preferred embodiment of the manufacturing method, a colored paper substrate is prepared by impregnating the paper substrate with a colored thermosetting resin.

[0290] In a preferred embodiment of the manufacturing method, the protective layer is at 1 g / m 2 With 100 g / m 2 The amounts in between include hard particles.

[0291] In a preferred embodiment of the manufacturing method, the thermosetting resin is a melamine-based resin. Melamine-based resins are preferred not only because of their excellent physical properties against abrasion, but also because of their clear transparency after hot pressing, without showing any fading.

[0292] In a preferred embodiment of the manufacturing method, the protective layer is at 1 g / m 2 With 100 g / m 2 The amounts in between include hard particles.

[0293] In a preferred embodiment, the method of manufacturing a decorative processed part includes the step of hot-pressing at least a core layer and a decorative layer, the decorative layer comprising a decorative pattern and paper provided with a thermosetting resin. Preferably, the method of the present invention forms part of a DPL (Direct Lamination) process as described above, wherein the decorative layer is picked up in a stack for extrusion together with a core layer and a balancing layer, and preferably also a protective layer. It is not excluded that the method of the present invention may form part of a CPL (Compact Lamination) or HPL (High Pressure Lamination) process, wherein the decorative layer is hot-pressed at least with a plurality of resin-impregnated core paper layers (e.g., so-called kraft paper) to form a substrate beneath the decorative layer, and wherein the resulting pressed and cured laminate or laminate, in the case of HPL, is bonded to another substrate, such as to a particleboard or MDF or HDF board.

[0294] In a preferred embodiment, a protective layer comprising a thermosetting resin is applied to the inkjet-printed decorative pattern, wherein the thermosetting resin may be a color thermosetting resin to reduce the amount of ink to be printed.

[0295] In a preferred embodiment of the manufacturing method, inkjet printing is performed using a single-pass inkjet printing process. This allows for high throughput (m³ / hour). 2 (Decorative processed parts). Alternatively, use multiple multi-pass inkjet printers.

[0296] Example

[0297] Examples of encoding methods for identifying digital fingerprint codes are described, as well as examples of decoding methods for identifying digital fingerprint codes.

[0298] Examples of identification encoding methods

[0299] Examples of preferred embodiments are described in detail below:

[0300] In this example, the focus is on the string message, but since all data is represented in bits, most of the methods in this section are independent of the type of data. The string message is converted into multiple binary data.

[0301] Using line thickness to represent position

[0302] The first step in encoding any kind of data is, in this example, choosing a way to represent the values ​​"1" and "0" given the medium. In this case, the given medium is the thickness of a line. Explore three possibilities:

[0303] a) The first way to represent a bit is as a fixed-length line segment, separated by shorter line segments, with three different levels of thickness: the smallest for the transition between two bits, the thickest for 1, and the one between them for zero. This way of representing bits is shown as Figure 1 The signal in.

[0304] b) A second way to represent bits is to use only two levels. One level is used to signal the change of the "current" bit, and the second is used to determine how long the bit has existed by making the time longer for a larger number of bits. To make it clearer, this way of representing bits is shown as Figure 2 The signal in.

[0305] Both of the aforementioned methods of representing bits have advantages and disadvantages.

[0306] The first approach has a fixed length between the beginnings of each bit, and there are signal changes at those positions. This makes bit detection easier because the recognition / decoding method knows it must find signal changes at regular intervals. It can also detect missed bits due to excessive distances between two consecutive bits. When the distance is too large, the recognition / decoding method can start looking for signal changes somewhere in the middle between the two bits.

[0307] The second method uses a different approach. While it does have a fixed length for each line segment, it doesn't have signal changes at regular intervals. Therefore, it's possible for the decoding method to skip several bits because it doesn't know when one bit ends and another begins. In other words, it can turn a 4 into a 3, and there's no good way to detect this error. On the other hand, the second method only works with two levels of coarseness, unlike the first method which has three levels.

[0308] Since the decoding intent is to be performed on digital photographs captured by digital imaging devices, which may be blurry, partially obscured, or more generally of poor quality, working in three levels can complicate the decoding of such digital photographs.

[0309] c) A third method of representing bits combines the advantages of the first and second methods. It operates with only two levels: one representing the bit and the other representing the transition to the next bit. The combination of the "bit" portion and its transition is always the same length. Therefore, signal changes occur at regular intervals, such as when transitioning from a transition to the next bit. The difference between zero and one is the length of each portion. For one, the bit portion is significantly longer than for zero. The transition portion of a bit is determined by subtracting the length of the bit portion from the total length used for the bit. Figure 3 The signal used for this encoding is shown in the figure.

[0310] Please note that this third way of representing bits is classified as unipolar line code.

[0311] Although other methods of representing bit or N-bit data can be used, the third method fully possesses the properties required for the recognition decoding method.

[0312] Error correction code

[0313] Although the third approach was chosen in this example to allow for easy decoding, errors are still possible. Omitted bits will be rare and can be corrected due to regular signal variations, but errors in bit values ​​are still very likely, for example, due to defects in the photograph. This is why the linear error-correcting code in this example is added to the encoding process using Hamming codes, due to their ease of use and their error-correcting rather than error-detecting capabilities. More complex codes, such as Hadamard codes, can be used. In this example, Hamming (7,4) codes with an information rate of 57% are used. An additional advantage of Hamming (7,4) codes is that most data consists of bytes (which are 8 bits), so input data often consists of multiples of four bits, which can be directly inserted into Hamming (7,4) codes. This is true, among other things, for each byte-long ASCII character that becomes 14 bits long after being encoded using Hamming codes. For example, the letter "A" (uppercase a) is shown as... Figure 5 The letter is encoded in the curve. This letter is ASCII (American Standard Code for Information Interchange) character 65 and is represented as a byte of "0100 0001". Using Hamming (7, 4) code, this becomes "1001100 1101001". This is entirely within the... Figure 5 The content shown in the middle image.

[0314] In coding theory, Hamming (7,4) code encodes 4 bits of data into a 7-bit linear error-correcting code by adding 3 parity bits. It is a member of a larger family of Hamming codes.

[0315] Enable data decoding

[0316] exist Figure 5In this context, different bits can be read from left to right, but this is not always the case. Figure 5 The image seen may be printed and hung top-down or vertically. To read and decode the curve, the end point of the curve must be distinguishable from its start point. This reading of the multiple N bits can be accomplished by evaluating the first and last bits, by adding a header and a tail to the multiple N bits. Note that both the header and tail are necessary, as using only one could result in data that happens to be identical to either the header or the tail. Furthermore, to decode the curve, it is necessary to know what kind of information is inside the curve. This can be done by adding another 4-bit codeword to the curve just after the header.

[0317] The encoding of the content in this example (a string of ASCII characters) will go through the following steps:

[0318] 1. ASCII characters are converted into multiple 8-bit data. For example, "A" becomes "0100 0001";

[0319] 2. Prefix the content with a 4-digit header sequence. For example, "0100 0001" becomes "0001 0100 0001";

[0320] 3. Add the corresponding tail sequence. ("0001" has four ones after encoding, so its tail is "0000"), for example, "0001 0100 0001" becomes "0001 0100 0001 0000";

[0321] 4. Encode the whole using Hamming (7, 4) code, for example, “0001 0100 0001 0000” becomes “1101001 1001100 1101001 0000000”.

[0322] The resulting codewords were described as follows: Figure 6 On the curve in the middle.

[0323] Examples of identification decoding methods

[0324] Examples of preferred embodiments are described in detail below:

[0325] Preprocessing the photos

[0326] In this example, the photograph is in RGB format. Given the varying lighting conditions—different curves, colors, resolutions, and angles—the input to the recognition and decoding methods can be expected to be highly diverse.

[0327] In the first stage, a photograph (602) of a digital fingerprint code (DF code) implemented by a digital imaging device is transformed into a binary image (612) using morphological operations. In this example, an adaptive thresholding method is used to introduce noise at various locations without a curve. To prevent this noise from interfering with the following operations, median blurring is performed to filter out white spots (622). Since median blurring can interrupt the curve at bit transitions, the final step of the processing is to perform expansion (632) to concatenate all bits again into a solid line curve. After these steps, it ends with a binary image that can be used as input to a more general algorithm that does not need to care about image details.

[0328] Find the skeleton of the curve

[0329] To read the contents of an image capture curve from the captured digital fingerprint code, it is necessary to follow the curve and check its thickness at each point, as computers cannot easily position themselves like humans. Therefore, the next step in this example is to find the path through the middle of the curve. It is quite clear that for the purposes of this application, the requirement for connectivity within the skeleton is much more important, as the contents of the curve cannot be found without connectivity. Zhang-Suen's thinning algorithm has been found to give the best results as a thinning method. It always delivers fully connected curves, and thus provides a more reliable and robust alternative to a more direct approach.

[0330] Information about wire thickness

[0331] Since the data uses variable line thickness embedding, a method for understanding the line thickness in the preprocessed image, which is the result of photo preprocessing, is needed. An easy way to accomplish this is by taking the Euclidean distance transform of the preprocessed image. This transforms the value of each pixel into the distance from that pixel to the nearest black pixel. It's easy to see on the preprocessed image that this value will approximate half the thickness in the middle of the curve. Then, the curve is followed from start to finish. At each position on the curve, the value of the distance transform at that pixel position is stored. The set of these values ​​(in the order they were found) can be interpreted as a one-dimensional signal that varies with position along the path. This signal corresponds to the noisy line thickness along the path, and we need this information to obtain the embedding content. After reading out the values, they are smoothed using a one-dimensional median filter to remove outliers and enhance interpretation.

[0332] Convert value to bit

[0333] After obtaining the smoothing value, the method for decoding the digital fingerprint code captured in the image begins by interpreting it using the peak values ​​in the one-dimensional signal as bits. In this example, it is accomplished in two steps:

[0334] a) Search for peak locations.

[0335] b) By examining the length and width of the peaks, the data is decoded into multiple N-bit data, which are binary data.

[0336] If the plurality of N-bit data is decoded from the image capture curve, the plurality of N-bit data is converted into the content of the curve embedded with digital fingerprint code.

[0337] Other preferred embodiments

[0338] This invention can therefore include a two-dimensional shape recognition method to determine the shape of a digital fingerprint code, and if a change is found in the determined one-dimensional signal, the recognition decoder can examine the shape forming the thickness at that location. This can introduce additional facilities for embedding additional N bits of data and security into the digital fingerprint printed code. The recognition encoder can therefore select from a number of shapes to transform the thickness of a portion of the first segment into a determined thickness using the selected shape. A preferred two-dimensional shape recognition method is the SKS algorithm disclosed by Karthik Krish and Wesley Snyder in “A Shape Recognition Algorithm Robust to Occlusion: Analysis and Performance Comparison”, September 13, 2007. Furthermore, other two-dimensional shape recognition methods can be used, such as shape context methods, Hu moment methods, and curvature scale space matching methods.

[0339] The thickness of the embedded code on the curve forming a digital fingerprint print can itself include identification codes such as QR codes, barcodes, or digital fingerprint print codes.

[0340] A defined image capture curve can be formed using high contrast in an image; therefore, the steps for determining the image capture curve may include contrast-changing methods for determining the curve in the image capture digital fingerprint code.

[0341] The determining curve in the document of the identification encoding method is preferably generated by a planar filled line pattern generator, so the determining curve is a planar filled line pattern, and more preferably it is generated by the Lindenmayer system.

[0342] Flat fill line pattern

[0343] To prevent forgery, geometrically repeating patterns are filled in areas of the document space derived from the document (most of which are filled with background patterns). The complexity of these geometrically repeating patterns is difficult to reproduce and therefore acts as a security feature. These geometrically repeating patterns in the filled areas are called planar fill line patterns.

[0344] A planar fill line pattern defined by one or more lines is a geometrically repeating pattern of an area (also called space) in the document space of a document that can be filled. This area can be of any shape, but it is completely filled with the planar fill line pattern. Preferably, this area is rectangular. The lines or portions of the lines in the planar fill line pattern can have any color, thickness, or can be defined as dashes. Preferably, the planar fill line pattern is a single line filling the area.

[0345] In a preferred embodiment of the invention, the planar fill line pattern is a space fill curve or FASS curve, space fill curve, self-similar fractal curve, de Rham curve, space fill tree, maze, meander pattern, Coran pattern, staggered pattern, or meander. In the invention, the planar fill line pattern (105) has constraints for including repeating sub-patterns that define lines bounded by two different endpoints, and preferably, the planar fill line pattern itself is a line bounded by two different endpoints.

[0346] Interlocking patterns are a design that has been used historically in many places and by different cultures for decoration, such as concentric knots, Celtic knots, Islamic interlocking patterns, or Croatian interlocking patterns. Interlocking patterns are mostly made of loops, braids, and / or knots.

[0347] In the prior art, planar fill line pattern generators are used to generate planar fill line patterns, where these geometrically repeating patterns (also known as periodic patterns) are generated by software methods that often include mathematical methods. In a preferred embodiment, the planar fill line pattern generator is the Lindenmayer system.

[0348] In this invention, a planar fill line pattern is generated and defined as multiple drawing instructions. A drawing instruction is an instruction to draw an image in document space. This image is often a geometric primitive, such as a point, line, arc, or polygon. The drawing instructions can be vector drawing instructions or linear drawing instructions. The generated multiple drawing instructions may also include other instructions, such as jumping to an absolute or relative position in document space, a storage location, a drawing direction, defining an angle, etc.

[0349] Some examples of computer-generated geometric repeating patterns are Taprats used for Islamic interlacing patterns. TM (http: / / sourceforge.net / projects / taprats), Knotter for Celtic knots TM (http: / / sourceforge.net / projects / knotter), Amaze for maze generation TM(http: / / sourceforge.net / projects / qtamaze). In Extended PastingScheme for Kolam Pattern Generation by ROBINSON THAMBURAJ. FORMA. The Kolam pattern generator was disclosed in 2007, vol.22, pp.55-64.

[0350] The resulting planar fill line pattern can be cropped and / or scaled to a defined area of ​​the document space from the secure document after the overlay. This defined area can be of any shape.

[0351] The lines in the planar filled line pattern and the lines in the defined graphic objects (205, 207) of this invention preferably have a thickness between 1 μm and 10 mm. The thinner these lines are, the more difficult it is to forge secure documents.

[0352] The minimum distance between lines in a planar filled line pattern is preferably between 1 μm and 10 mm. The smaller the minimum distance between lines, the more difficult it is to forge the document.

[0353] In this invention, the space between the lines in the planar filled line pattern (105) and the lines in the defined graphic object is preferably between 1 μm and 10 mm. The smaller the space between the lines, the more difficult it is to forge the document.

[0354] Lindenmayer system

[0355] The Lindenmayer system, also known as the L-system, is a parallel rewriting system and a formal grammar. An L-system consists of letters that can be used to generate strings of symbols, a set of rules for expanding each symbol into a larger string of symbols, an initial string of "axioms" from which to be constructed, and a mechanism for transforming the generated strings into geometric structures. The symbols of the letters are preferably vector drawing instructions, such as Turtle Graphics, and the strings generated from the Lindenmayer system differ from the multiple step-by-step vector drawing instructions.

[0356] In the book published by Springer-Verlag in New York in 1990 and reprinted in 1996: The Algorithmic Beauty of Plants The L system is disclosed in the electronic version of (the author Przemyslaw Prusinkiewicz, Aristid Lindenmayer) (especially in Chapter 1).

[0357] The patterns generated by the L system are security-enabling graphic objects that will be used in security documents to prevent, for example, forgery. Because security patterns are defined by specific production rules and letter definitions, they are difficult to redesign on their own.

[0358] The recursive nature of the L-system rules leads to self-similarity, and thus fractal forms are easily described by the L-system, such as Hilbert curves or Sierpinski triangles.

[0359] In a preferred embodiment, the L system generates a space-filling curve. Space-filling curves are disclosed in BADER MICHAEL, *Space-Filling Curves: An Introduction With Applications in Scientific Computing*, edited by BARTH TJ et al. (SPRINGER, 2012, p. 278). In a preferred embodiment, the L system generates a space-filling curve selected from Hilbert curves, Lévy C-shaped curves, Koch curves, Peano curves, Gosper curves, dragon curves, and Moore curves.

[0360] Reference number list

[0361] Table 1

[0362] 100 Vertical axis 200 Horizontal axis 300 Multiple binary data 500 Digital fingerprint code 406 value "1" 405 Value "0" 400 curve 602 Image capture methods 605 Image capture digital fingerprint code 612 Threshold determination method 615 Threshold image capture digital fingerprint code 622 Fuzzy method 625 Capturing digital fingerprint codes from blurred thresholded images 632 Expansion methods 635 Dilatation blur thresholded image capture digital fingerprint code 900 User interface objects 901 User interface objects 902 User interface objects 903 User interface objects 904 User interface objects 905 User interface objects 906 User interface objects 907 User interface objects 908 User interface objects 909 User interface objects 910 user interface

Claims

1. A decorative workpiece selected from the group consisting of a kitchen panel, a floor panel, a furniture panel, a ceiling panel and a wall panel, wherein the decorative workpiece comprises a wood pattern comprising one or more nerve or grain defects; and wherein the one or more nerve or grain defects comprise an identification code for tracking and tracing the decorative workpiece; and wherein the identification code: - is embedded on the one or more nerve or grain defects; and - is not visible to the human eye at a certain observation distance; wherein the identification code is an inkjet printed identification code and the inkjet printed identification code comprises a plurality of N-bit data representing content; and wherein the plurality of N-bit data comprises a first N-bit data (N1) and a second N-bit data (N2) different on the one or more nerve or grain defects; and a coarseness (T N,1 ) of values (v N,i,1 ) from the first N-bit data (N1) on the nerve or grain defect is different from a coarseness (T N,2 ) of values (v N,i,2 ) from the second N-bit data (N2), and / or a length (L N,1 ) of values (v N,i,1 ) from the first N-bit data (N1) on the nerve or grain defect is different from a length (L N,2 ) of values (v N,i,2 ) from the second N-bit data (N2).

2. The decorative workpiece according to claim 1, wherein the wood pattern is not visible to the human eye at an observation distance greater than 20 centimeters.

3. The decorative workpiece according to claim 2, wherein the decorative workpiece comprises an additional thermoset resin and a wood-based core layer.

4. The decorative workpiece according to claim 1, wherein the decorative workpiece comprises a tongueless and groove joint.

5. The decorative workpiece according to claim 4, wherein the inkjet printed identification code has the same color as the one or more nerve or grain defects.

6. The decorative workpiece according to claim 1, wherein the content comprises a serial number of the decorative workpiece.

7. The decorative workpiece according to claim 1, wherein the wood pattern is not visible to the human eye at an observation distance greater than 50 millimeters.

8. The decorative workpiece according to claim 1, wherein the wood pattern comprises one or more water-based inks.

9. A tracking and tracing method for a decorative workpiece according to claim 1, the method comprising: decoding the identification code on the decorative workpiece.

10. The tracking and tracing method according to claim 9, by using a mobile phone or tablet computer for the decoding step.

Images